Towards a Maturity Model for Learning Analytics Adoption An Overview of its Levels and Areas

Resource type
Conference Paper
Authors/contributors
Title
Towards a Maturity Model for Learning Analytics Adoption An Overview of its Levels and Areas
Abstract
Learning Analytics is a new field in education whose adoption can bring benefits for teaching and learning processes. However, many higher education institutions may not be ready to start using learning analytics due to challenges such as organizational culture, infrastructure, and privacy. In this context, Maturity Models (MMs) can support institutions to systematize their processes, enabling them to progress successively in the learning analytics adoption. MMs are used in different fields to support the improvement of processes, describing them in terms of maturity levels, and identifying enhancements that could lead an organization to higher levels of such maturity. Thus, this paper presents an outline of a MM for Learning Analytics adoption in higher education institutions, describing its levels and areas, together with its development methodology.
Date
2020-07
Proceedings Title
2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT)
Conference Name
2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT)
Pages
122-126
Accessed
19/03/2024, 21:31
Library Catalogue
IEEE Xplore
Extra
ISSN: 2161-377X
Citation
Freitas, E., Fonseca, F., Garcia, V., Ferreira, R., & Gašević, D. (2020). Towards a Maturity Model for Learning Analytics Adoption An Overview of its Levels and Areas. 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT), 122–126. https://doi.org/10.1109/ICALT49669.2020.00059